A blog about learning go and learning computer go. A go beginner tries to improve his game and use their software engineering skills to build a computer go player. Entries about their go reading, computer go reading, go playing, go improvement, go concepts (seki, ko, miai, etc) and progress building the computer go player.

Tuesday, June 14, 2005

"Monte Carlo Go" by Bernd Brügmann

I've just read "Monte Carlo Go" by Bernd Brügmann, which uses simulated annealing to evaluate positions when playing go. The system is not particularly effective, mainly because of the very slow cooling required to play well.

I know it goes completely against all the theory behind the solution, but I can't help but think that maybe one could do better than random plays. I particular, it seems to me that the best ranked positions from not n are likely to at least be candidates for move n+1.

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